“Prices, Interest Rates, and Exchange Rates in Equilibrium” (International Parity Conditions) Table of Content Executive Summary… 31. Introduction… 42. Literature Review… 63.
Findings and Analysis: … 10 a. PPP… 10 b.
FE… 12 c. IFE… 144.
Conclusion & Recommendations… 16 Bibliography… 17 Appendix A. Historical Data… 18 Table of Figures Figure 1.
International Parity Conditions Figure 2. Scatter Diagram for PPP Figure 3. Time-series data for inflation rates differential and exchange rate change Figure 4. Regression Plot for PPP Figure 5. Scatter Diagram for FE Figure 6.
Time-series data for inflation and interest rates differentials Figure 7. Regression Plot for FE Figure 8. Scatter Diagram for IFE Figure 9. Time-series data for interest rates differentials and exchange rate change Figure 10. Regression Plot for IFE Executive Summary This assignment is aimed at examining the evidence for three of the relationships that underpin (explicitly or implicitly) much of international macroeconomics. The first is purchasing power parity (PPP), or the hypothesis that there exists a constant long-run equilibrium real exchange rate.
The second is Fisher Effect, which tests the relationship between difference in inflation rates and difference in nominal interest rates. The third establishes a relationship between real exchange rates and real interest rate differentials or International Fisher Effect. The tests are conducted on a basis of two economies: United States and Kazakhstan. The results are obtained using graphs and regression models, which significantly increase the power of the tests.
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Chaos in The Currency Markets: Currency Crisis of The EMS 1. What does the crisis of September 1992 tell you about the relative abilities of currency markets and national governments to influence exchange rates? The currency markets and national governments both have abilities to influence exchange rates. Like other financial markets, foreign exchange markets react to any news that may have a ...
The empirical evidence is evaluated on the basis of historical data for the period of 1999-2003. The paper is divided into two main parts. The first part contains analysis of the historical data about interest rates, exchange rates, and 3-month T-bills (Kazakhstani name: MEKKA M) in two countries: Kazakhstan and USA. The second part gives implications based on the results of analysis. Introduction The core of international finance theory lies in international parity conditions. They bring together prices, interest rates, and exchange rates.
As expected rate of change in the spot exchange rate, differential rates of national inflation and interest, forward discount or premium are all interrelated, a change in one of them leads to a change in all the rest, so that the first variable changes again. In our work we test whether International Parity Conditions hold in the context of the Kazakhstani economy. In our research we intend to examine the theory of Purchasing power parity, Fisher effect, International Fisher effect, Interest rate parity, and Forward rate as an unbiased predictor of the future spot rate. Scope of the study For the purposes of this study we obtain time series data on the American and Kazakhstani interest rates, inflation rates, and exchange rate statistics on quarterly basis for five years (1999-2003).
Limitations In this paper we consider parity conditions between US and Kazakhstan. Kazakhstani Stock Exchange doesn’t trade forward contracts; therefore we are not able to test such conditions as forward rate as unbiased predictor of the future spot rate and interest rate parity. Furthermore, some months T-bills were not issued, that’s why we will omit these months in our analysis. Significance of the study The study represents an empirical evidence of international parity conditions.
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It goes without saying, that interest rates influence our decisions, and affect many activities in our lives. Interest rates can be expressed as a percentage of the amount borrowed or saved. People always try to be well-informed about changes in economy and finance. They say that it helps them to make better decisions about their personal finance. It is evident that interest rates affected the ...
It helps explain the long run trend in an exchange rate. This study will help to understand how multinational business is conducted and financed. Literature review Alan Shapiro in “Multinational Financial Management” affirms that there are five parity conditions resulted from arbitrage activities based on law of one price: Purchasing Power Parity (PPP); The Fisher Effect (FE); The International Fisher Effect (IFE); Interest Rate Parity (IRP); Unbiased Forward Rate (USR).
Michael H. Moffett, et al in “Fundamentals of Multinational Finance” say that the PPP is not particularly helpful in determining what the spot rate is today, but that the relative change in prices between countries over a period of time determines the change in exchange rates. Moreover, if the spot rate between 2 countries starts in equilibrium, any change in the differential rate of inflation between them tends to be offset over the long run by an equal but opposite change in the spot rate.
As for empirical tests, they say that both relative and absolute purchasing power parity show that for the most part, PPP tends to not be accurate in predicting future exchange rates. Two general conclusions can be drawn from the tests: o PPP holds up well over the very long term but is poor for short term estimate so The theory holds better for countries with relatively high rates of inflation and underdeveloped capital markets. Georgios E. Chortareas and Rebecca L. Driver in “PPP and the real exchange rate-real interest rate differential puzzle revisited: evidence from non-stationary panel data” state that the results show that there is little direct evidence to support PPP, i. e.
the proposition that the real exchange rate is constant, or at least mean-reverting, in the long run. This evidence is obtained by examining the of the real exchange rate. The failure to find PPP contradicts the evidence from recent applications of non-stationary panel techniques to the real exchange rate. It suggests that, even with the new more powerful techniques, finding PPP may still be heavily sample-dependent. The Fisher Effect states that nominal interest rates (r) are a function of the real interest rate (a) and a premium (i) for inflation expectations: R = a + i.
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Real Rates of Interest should tend toward equality everywhere through arbitrage; with no government interference nominal rates vary by inflation differential or rh – rf = ih – if. According to the Fisher Effect, countries with higher inflation rates have higher interest rates. Jafar A. Khondaker in “Real Interest Rate Parity and the Modeling of the Real Exchange Rate” provides a clear understanding of the meaning of real interest rate parity. It then presented an accounting framework to argue that real interest rates cannot equalize even in the long run in the presence of country- and currency-premium. He can, however, conclude that whatever evidence was uncovered using Johansen’s maximum likelihood-based co integration tests is consistent with the hypothesis that even in the long run real interest rates between the five industrialized countries in the sample do not become equal.
The evidence is rather consistent with a parity relationship that may include a risk premium. Frankel (1993) discusses the relationship between the different theories and assumptions, while Meese and Rogoff (1988) probably provides the classic derivation of the relationship between real exchange rates and real interest rates investigated here. However, despite the theoretical and intuitive appeal both of the real exchange rate real-interest rate differential relationship and of its underlying components, the empirical evidence for these propositions (either separately or collectively) has at best been mixed. The American Graduate School of International Management “Thunderbird” (2003) states that there is also an effective exchange rate, which is a multilateral rate that measures the overall nominal value of the currency in the foreign exchange market. For example, the effective U. S.
dollar exchange rate combines many bilateral exchange rates using a weighting scheme that reflects the importance of each country’s trade with the United States. Several institutions (for example, the International Monetary Fund, the Federal Reserve Board) regularly calculate and report the effective exchange rates. There is also a real effective exchange rate, adjusting for multilateral PPP relationships. The relationship between exchange rates and nominal interest rates is captured in two simple propositions: (1) the covered interest parity theorem (CIP) which deals with a no-arbitrage equilibrium in international financial markets, and (2) the speculative efficiency hypothesis and the resulting uncovered parity theorem (UIP) which deals with a speculative equilibrium in international financial markets. Covered interest parity is the mechanism through which an equilibrium relationship is established between spot and forward exchange rates, and risk-equivalent domestic and foreign nominal interest rates. This relationship is also sometimes referred to as the interest rate parity theorem or the covered interest arbitrage condition.
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Empirical tests generally show that the forward rate is not a very good predictor of the level of the future spot rate (it explains about 10% of the change in the actual future exchange rates).
However, evidence is strong that the forward rate does a better job of predicting at least the direction of changes to future spot rates than do about two-thirds of the better known foreign exchange forecasting services, making it one of the better predictors around. The market for foreign exchange is the largest market in the world. Transactions in the foreign exchange market well exceed $1 trillion daily. The market operates almost twenty-four hours a day, so that somewhere in the world, at any given time, there is a market open in which you can trade foreign exchange. Nearly nine-tenths of the trades across the world involve the U.
S. dollar. The reasons for this are three-fold. One, the U.
S. dollar is still the most heavily traded currency worldwide and is the reference currency for denominating the prices of a number of globally traded products such as oil, aircraft, gold, and so forth. Two, triangular arbitrage opportunities are rarely present in the foreign exchange markets for the heavily traded currencies. In other words, if the price of currency A is known with respect to B and C, the price of B in terms of C is automatically determined, otherwise there would be a costless arbitrage opportunity-traders quote prices as though such arbitrage opportunities are not present and thus, the arbitrage opportunity is non-existent in the first place. Three, the dollar-based quotation dramatically reduces information complexity.
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It is far easier for a trader to remember, say, eight currency quotes against the U. S. dollar and derive the rest by assuming absence of triangular arbitrage opportunities, rather than remember the 9 8/2 = 36 pairwise currency quotes (including those for the U. S.
dollar) that actually prevail. Both direct and indirect quotes (against the U. S. dollar) are simultaneously used in foreign exchange markets, depending on the currency involved. For instance, the Euro and the British pound are quoted in direct terms (number of dollars per currency unit), while the Kazakhstani Tenge is quoted indirectly (the number of tenge per dollar).
There is a large volume of research on the underlying fundamentals that determine currency values.
In the short run (hour to hour, or even over days), such fundamentals do not seem to matter much, since currency trading and spec u lati on are driven almost entirely by technical considerations. This is consistent with the fact that direct deals account for a large proportion of foreign exchange transactions. It is for these reasons that currency forecasting is an exercise that is, at best, tenuous and, at worst, somewhat pointless. Therefore, the list of variables and the effects indicated above should be used with a fair amount of caution. The role of an MNE manager is not to forecast exchange rates; rather, it is (a) to appreciate the fact that the uncertainty induced by this aspect of the international environment is real and ubiquitous, and (b) to manage and plan for the effects of this uncertainty on the operations and performance of the firm.
This in turn requires us to understand the different ways in which Mines are exposed to exchange rates. If we combine the insights from RPPP and UIP, we obtain another interesting implication, known as the international Fisher effect. It says that real interest rates, i. e. , the nominal interest rates adjusted for inflation expectations, must be the same both at home and abroad. In other words, it implies the following: when goods markets are in equilibrium resulting from RPPP and capital markets are in equilibrium resulting from UIP, real productivity of capital, i.
e. , the NPV of a similar project, must be the same across all countries where these two parity conditions hold! Findings and Analysis Purchasing Power Parity This graph represents the distribution of the historical data correlation on percent difference in inflation rates between USA and Kazakhstan and percent change in the spot exchange rate for US dollar. As we can see from the exhibit, our distribution is clustered to the right of the PPP line. The deviation is significant. Therefore, we deduce that inflation rates in US have been persistently lower than those in Kazakhstan.
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As to the change in the spot exchange rate, since January 1999 to November 2002 Tenge was depreciating against dollar, hence we see strengthening of Tenge. However, we see some significant deviations from the general trend. A distant point on the graph (-23. 18; 2.
39) represents the moment when Kazakhstan changed exchange rate policy. The acceptance of the floating exchange rate led to sharp change in the exchange rate. The same tendency for inflation rates difference and exchange rate change can be observed. They rise and fall simultaneously except beginning of the graph, which is explained by the introducing the floating exchange rate already discussed before.
There is a deviation between two lines which means that exchange rate change is determined not only by inflation rates difference, but also by other factors. For our purpose of testing the theory of equilibrium, we intend to implement regression analysis. The graph below represents the regression run with the aim of testing if the theory holds in case of Kazakhstan. For the purposes of this regression we set the value of ‘a equal to 0. Therefore, we want to see ^a to be equal to 1. This would prove the fact that PPP holds in this case.
As seen from the table below ^a is equal to 0, 0780782, which is significantly lower than 1. This means that spot exchange rate changes at a greater pace than inflation rate. Coefficients Standard Error Intercept 0 #N/AExchange Rate Change 0, 0780782 0, 280666729 From the regression analysis we conclude that PPP theory doesn’t hold in case of Kazakhstani Tenge versus US dollar. Fisher Effect From theory we know that the nominal interest rate equals the required real rate of return plus compensation for expected inflation. If we compare two countries the difference in nominal rates between two countries is equal to difference in inflation rates. This graph shows that interest rates were changing in accordance with the change in the inflation rates.
They were keeping up with the change, i. e. the real interest rate corresponded to the implied interest rate. From the scatter gram we infer that the condition more or less holds. Therefore, our test results imply that Fisher effect holds in the Kazakhstani context.
From the graph we can see that in 1999 there were contradicting data, then inflation and interest rates differential follow the same trend. Nevertheless, it is difficult to say because T-bills were not issued for several months. In our testing we again set ‘a equal to 0. Therefore ^a should be equal or close to 1, if the condition holds. The coefficients obtained from the regression analysis are presented below. ^a is equal to 0, 540670118.
Coefficients Standard Error Intercept 0 #N/Interest differential 0, 540670118 0, 128036191 According to the regression analysis, the condition doesn’t hold. International Fisher Effect This graph represents the relationship of the percent difference in the interest rates and percent change in the spot exchange rate of Tenge for US dollar. The points fall far from equilibrium line. Again, we see that deviation from the preceding period is significant in several cases.
These are explained by the fact of the change of the exchange rate policy. On the graph of time-series data there is no clear trend that exchange rate change follow interest rates differential. However, the regression analysis provides the opposite result. The fitted line shows that the condition holds. In this case ^a is close to 1 (1, 175796189).
Coefficients Standard Error Intercept 0 #N/AExchange Rate Change 1, 175796189 0, 355906816 On the graph you can see that the fit line obtained is very close to the IFE line. Conclusion & Recommendations Due to mentioned problem (absence of the information regarding forward rates) we were able to analyze only three parity conditions: purchasing power parity, Fisher effect, and international Fisher effect. The analysis has shown that there is no real evidence of these theories. This was because very short time horizon has been used. We know from the theory that PPP holds usually in the long run and not really useful for predicting exchange rates in the short run. During analysis we have observed some trends in favor of that parity conditions.
These tendencies have been seen from the time-series graphs, where it is easier to observe co-movements of exchange rate changes, interest and inflation rate differentials. The best example of co-movement in time-series graph was for PPP testing. Scatter diagram applied in the beginning of our analysis indicated distribution of points around PPP, Fisher and IFE lines. In case of testing Fisher effect points fall most closely to the parity line. Regression analysis showed that International Fisher Effect holds among parity conditions, which is rather strange because if PPP does not hold, IFE will not hold since IFE is based on PPP.
The contradicting results were got because T-bills were not issued for several months, and these months were eliminated from our analysis of IFE, whereas in testing PPP all data have been used. The international Fisher effect theory suggests that currencies with higher interest rates will depreciate because the higher rates reflect higher expected inflation. Hence, investors hoping to capitalize on a higher foreign interest rate should earn a return no better than what they would have earned domestically. Kazakhstan had interest rates higher than in USA.
The Fisher effect explains it by higher rates of inflation in Kazakhstan. According to the fact that FE and IFE theories hold, there is no difference regarding where to invest to or borrow from among two countries: Kazakhstan and USA. Although we didn’t prove the parity conditions by all means, it is useful to study these theories in order to understand reasons which underlie exchange rates movements. Bibliography 1.
Republic of Kazakhstan: Statistical Appendix. IMF Country Report # 04/363, November, 2004. 2. Michael H. Moffett, Arthur I. Stonehill, David K.
Eit eman, “Fundamentals of Multinational Finance”3. Jafar A. Khondaker, “Real Interest Rate Parity and the Modeling of the Real Exchange Rate”4. Georgios E.
Chortareas and Rebecca L. Driver, “PPP and the real exchange rate-real interest rate differential puzzle revisited: evidence from non-stationary panel data”, 20015. Alan Shapiro “Multinational Financial Management” 7 th Edition J. Wiley & Sons, 20026.
Adler, Michael and Bruce Lehmann, (1983), “Deviation from Purchasing Power Parity in the Long Term”, Journal of Finance, 38 (No. 5, December) 7. Lee, Daniel Y. , (1999),” Purchasing Power Parity and Dynamic Error Correction Evidence from Asia Pacific Economies”, International Review of Economics and Finance, 8 (No. 3, June) 8. Moos a, I mad A.
and Razzaque H. Bhatt i, (1997), International Parity Conditions (New York: St. Martin’s Press) Appendix A. Historical Data Kazakhstan USA Year Month Exchange Rate d i d i Exchange rate change Inflation rates difference Interest rates difference 1999 January 84. 57 1 26. 3 1.
67 4. 37 -1. 3301 0. 67 -21. 93 February 85. 71 -0.
3 26. 3 1. 61 4. 55 -1. 9561 1. 91 -21.
75 March 87. 42 -1. 2 26. 3 1. 73 4. 37 -23.
1810 2. 93 -21. 93 April 113. 8 2. 8 2. 28 4.
43 -4. 4821 -0. 52 May 119. 14 3. 9 2. 09 0 -9.
6603 -1. 81 June 131. 88 9. 8 1.
96 4. 65 -0. 4304 -7. 84 July 132. 45 11. 2 21.
6 2. 14 4. 62 0. 4855 -9. 06 -16.
98 August 131. 81 11. 9 21. 6 2. 26 4. 84 -2.
9238 -9. 64 -16. 76 September 135. 78 12. 8 2. 63 4.
74 -3. 8453 -10. 17 October 141. 21 14. 3 2. 56 4.
97 1. 4731 -11. 74 November 139. 16 16. 3 16. 6 2.
62 5. 15 0. 7019 -13. 68 -11. 45 December 138. 19 17.
8 16. 6 2. 68 5. 17 -0. 6256 -15. 12 -11.
432000 January 139. 06 19. 8 16. 7 2. 74 5.
53 -0. 6004 -17. 06 -11. 17 February 139. 9 20. 2 16.
4 3. 22 5. 62 -1. 0748 -16. 98 -10. 78 March 141.
42 20. 4 16 3. 76 5. 72 -0.
5555 -16. 64 -10. 28 April 142. 21 15. 6 15. 6 3.
07 5. 66 -0. 0562 -12. 53 -9. 94 May 142.
29 14. 7 14. 6 3. 19 5. 48 -0. 2524 -11.
51 -9. 12 June 142. 65 10. 2 13. 1 3.
73 5. 71 -0. 0980 -6. 47 -7. 39 July 142.
79 9. 5 12. 6 3. 66 6. 03 0. 1332 -5.
84 -6. 57 August 142. 6 10 9. 9 3.
41 6. 13 -0. 0631 -6. 59 -3. 77 September 142. 69 9.
8 9. 5 3. 45 6. 05 0. 0842 -6. 35 -3.
45 October 142. 57 10. 4 7. 6 3. 45 6. 19 -0.
9999 -6. 95 -1. 41 November 144. 01 10. 2 7. 5 3.
45 6. 03 -0. 6691 -6. 75 -1. 47 December 144. 98 9.
8 6. 8 3. 39 5. 73 -0. 2751 -6.
41 -1. 072001 January 145. 38 8. 2 6.
7 3. 73 4. 86 0. 0344 -4. 47 -1. 84 February 145.
33 8. 8 6. 6 3. 53 4. 73 -0. 1031 -5.
27 -1. 87 March 145. 48 9. 6 5. 6 2. 92 4.
2 -0. 0412 -6. 68 -1. 4 April 145.
54 9. 2 5. 4 3. 27 3. 86 -0. 4038 -5.
93 -1. 54 May 146. 13 9. 3 5. 2 3. 62 3.
55 -0. 3138 -5. 68 -1. 65 June 146. 59 9.
2 5 3. 25 3. 57 -0. 1158 -5. 95 -1.
43 July 146. 76 9. 1 4. 9 2.
72 3. 46 -0. 2786 -6. 38 -1. 44 August 147.
17 9 4. 8 2. 72 3. 3 -0.
3588 -6. 28 -1. 5 September 147. 7 8.
9 5. 1 2. 65 2. 35 -0. 2229 -6.
25 -2. 75 October 148. 03 8. 7 5. 4 2. 13 2.
01 -0. 3568 -6. 57 -3. 39 November 148. 56 8. 5 1.
9 1. 75 -1. 1708 -6. 6 December 150. 32 8. 4 1.
55 1. 71 -0. 8574 -6. 85 2002 January 151. 62 6 5. 3 1.
14 1. 73 -0. 2631 -4. 86 -3. 57 February 152. 02 5.
8 1. 14 1. 76 -0. 1314 -4. 66 March 152.
22 5. 6 1. 48 0 -0. 3470 -4. 12 April 152. 75 5.
4 5. 3 1. 64 1. 74 -0. 1373 -3. 76 -3.
56 May 152. 96 5. 4 5. 3 1.
18 1. 71 -0. 1110 -4. 22 -3. 59 June 153. 13 5.
5 1. 07 1. 67 -0. 5003 -4.
43 July 153. 9 5. 6 1. 46 1. 68 -0.
2657 -4. 14 August 154. 31 5. 7 1. 8 1. 66 -0.
1359 -3. 9 September 154. 52 5. 7 1. 51 1.
54 0. 0712 -4. 19 October 154. 41 5. 8 2. 03 1.
42 0. 0194 -3. 77 November 154. 38 5. 8 2. 2 1.
2 -0. 8350 -3. 6 December 155. 68 5. 9 2. 38 1.
2 0. 2189 -3. 52 2003 January 155. 34 6. 9 2. 6 1.
16 1. 3043 -4. 3 February 153. 34 7 2.
98 1. 18 1. 2012 -4. 02 March 151. 52 7 3.
02 1. 12 -0. 3027 -3. 98 April 151. 98 7 2. 22 1.
11 0. 6623 -4. 78 May 150. 98 6. 9 2.
06 1. 09 1. 3221 -4. 84 June 149. 01 6. 7 2.
11 0. 89 1. 3949 -4. 59 July 146. 96 6. 4 2.
11 0. 94 0. 1636 -4. 29 August 146. 72 6. 3 2.
16 0. 96 -0. 8649 -4. 14 September 148 6. 3 6 2. 32 0.
93 0. 1218 -3. 98 -5. 07 October 147.
82 6. 3 2. 04 0. 94 0. 5647 -4.
26 November 146. 99 6. 4 1. 77 0. 91 1. 5826 -4.
63 December 144. 7 6. 4 1. 88 0.
93 -4. 52.
